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Conference papers
A Fully Connected Neural Network to Mitigate 200G DP-16-QAM Transmission System Impairments
Clara Catanese 1
Author
Reda Ayassi 1
Author
Erwan Pincemin 1
Author
Yves Jaouën 2, 3, 4
Author IdHAL : yjaouen
1
Orange Labs [Lannion] (Technopole Anticipa 2 avenue Pierre Marzin 22300 LANNION - France)
- France Télécom (France)
2
IP Paris - Institut Polytechnique de Paris (France)
3
GTO - Télécommunications Optiques (Télécom Paris 19 Place Marguerite Perey 91120 Palaiseau - France)
- LTCI - Laboratoire Traitement et Communication de l'Information (Télécom Paris 19 Place Marguerite Perey 91120 PALAISEAU - France)
- IMT - Institut Mines-Télécom [Paris] (37-39 Rue Dareau, 75014 Paris - France)
- Télécom Paris (19 Place Marguerite Perey 91120 Palaiseau - France)
4
COMELEC - Département Communications & Electronique (46, rue Barrault
75013 Paris - France)
- Télécom ParisTech (46 rue Barrault 75634 Paris Cedex 13 - France)
Document type :
Conference papers
Domain :
Complete list of metadata
https://hal.telecom-paris.fr/hal-02968692
Contributor : Yves Jaouen Connect in order to contact the contributor
Submitted on : Friday, October 16, 2020 - 6:59:05 AM
Last modification on : Wednesday, October 27, 2021 - 6:44:45 AM
Contributor : Yves Jaouen Connect in order to contact the contributor
Submitted on : Friday, October 16, 2020 - 6:59:05 AM
Last modification on : Wednesday, October 27, 2021 - 6:44:45 AM
Identifiers
- HAL Id : hal-02968692, version 1
- DOI : 10.1364/SPPCOM.2020.SpTh3I.1
Citation
Clara Catanese, Reda Ayassi, Erwan Pincemin, Yves Jaouën. A Fully Connected Neural Network to Mitigate 200G DP-16-QAM Transmission System Impairments. Signal Processing in Photonic Communications, 2020, Washington, France. SpTh3I.1, ⟨10.1364/SPPCOM.2020.SpTh3I.1⟩. ⟨hal-02968692⟩
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